Medial temporal tau predicts memory decline in cognitively unimpaired elderly

Abstract Alzheimer’s disease can be detected in living people using in vivo biomarkers of amyloid-β and tau, even in the absence of cognitive impairment during the preclinical phase. [18F]-MK-6420 is a high-affinity PET tracer that quantifies tau neurofibrillary tangles, but its ability to predict cognitive changes associated with early Alzheimer’s disease symptoms, such as memory decline, is unclear. Here, we assess the prognostic accuracy of baseline [18F]-MK-6420 tau-PET for predicting longitudinal memory decline in asymptomatic elderly individuals. In a longitudinal observational study, we evaluated a cohort of cognitively normal elderly participants (n = 111) from the translational biomarkers in ageing and dementia study (data collected between October 2017 and July 2020, with a follow-up period of 12 months). All participants underwent tau-PET with [18F]-MK-6420 and amyloid-β PET with [18F]-AZD-4694. The exclusion criteria included the presence of head trauma, stroke or other neurological disorders. There were 111 eligible participants selected based on the availability of amyloid-β PET, tau-PET, MRI and APOEɛ4 genotyping. Among these participants, the mean standard deviation age was 70.1 (8.6) years; 20 (18%) were tau-PET-positive and 71 of 111 (63.9%) were women. A significant association between the baseline Braak Stages I–II [18F]-MK-6240 standardized uptake value ratio positivity and change in composite memory score were observed at the 12-month follow-up, after correcting for age, sex and years of education [logical memory and Rey Auditory Verbal Learning Test, standardized beta = −0.52 (−0.82–0.21), P < 0.001, for dichotomized tau-PET and −1.22 (−1.84−(−0.61)], P < 0.0001, for continuous tau-PET]. Moderate cognitive decline was observed for A + T + over the follow-up period, whereas no significant change was observed for A−T+, A + T- and A-T-, although it should be noted that the A−T + group was small. Our results indicate that baseline tau neurofibrillary tangle pathology is associated with longitudinal changes in memory function, supporting the use of [18F]-MK-6420 PET to predict the likelihood of asymptomatic elderly individuals experiencing future memory decline. Overall, [18F]-MK-6420 PET is a promising tool for predicting memory decline in older adults without cognitive impairment at baseline. This is of critical relevance as the field is shifting towards a biological model of Alzheimer’s disease defined by the aggregation of pathologic tau. Therefore, early detection of tau pathology using [18F]-MK-6420 PET provides us with hope that living patients with Alzheimer’s disease may be diagnosed during the preclinical phase before it is too late.


Introduction
Post-mortem studies show that amyloid-β (Aβ) plaques and tau neurofibrillary tangles, the defining hallmarks of Alzheimer's disease, are commonly observed in cognitively unimpaired (CU) elderly. 1,2 This suggests that there is a time window-a preclinical phase-where biological Alzheimer's disease can be detected in the absence of clinically significant cognitive decline using in vivo biomarkers of Aβ and tau. 3,4 With the recent FDA approval of the first tau tracer, [ 18 F]-flortaucipir (AV-1451 or T807), Alzheimer's disease molecular imaging is approaching clinical use. 5 Specifically, in vivo tau biomarkers derived from PET imaging modalities have shown promise as predictors of future cognitive changes prior to the clinical onset of dementia symptoms. 3,6,7 The ability to predict memory decline in CU individuals is an important step in defining and detecting biological Alzheimer's disease in vivo and during the preclinical phase. 8 Previous cross-sectional and longitudinal neuroimaging studies have demonstrated an association between tau pathology and cognitive decline in the CU elderly. [9][10][11] However, the [ 18 F]-flortaucipir tau-PET tracer used in these studies is prone to age-related off-target binding and its uptake only aligns accurately for Braak Stages IV or higher, suggesting limited sensitivity towards early tau accumulation. 12,13 The emergence and use of [ 18 F]-MK-6420 in clinical studies have shown subnanomolar affinity towards detecting tau neurofibrillary tangles in Alzheimer's disease and decreased non-specific binding in the brain. 6,14 This enables greater detection of early tau pathology in CU individuals during the asymptomatic preclinical period, allowing for a better understanding of its association with cognition and other Alzheimer's disease biomarkers.
In this study, we use the high-affinity tau-PET tracer [ 18 F]-MK-6420, focusing on imaging the medial temporal regions to detect very early tau in CU elderly, as opposed to the temporal meta-region of interest for later tau aggregation, at levels observed in Alzheimer's disease. 10 Specifically, we examined the prognostic accuracy of baseline [ 18 F]-MK-6420 PET for predicting longitudinal memory decline in initially CU elderly, who have been stratified based on the presence of a tau-PET signal in the medial temporal lobe.

Participants
CU participants (n = 111), defined by a clinical data repository of zero, were recruited for the translational biomarkers in ageing and dementia cohort as part of the McGill Centre for Studies in Ageing, which investigates biomarker trajectories and interactions as initiators of dementia. 15

PET image acquisition and processing
Each participant underwent a T 1 -weighted MRI, which was utilized for co-registration. PET scans were obtained using the Siemens high-resolution research tomography at the Montreal Neurological Institute. The [ 18 F]-MK-6240 images were acquired 90-110 min after injection and scans were reconstructed via the use of the ordered subset expectation maximization algorithm on a 4D volume with four frames (4 × 300 s). The [ 18 F]-AZD-4694 images were acquired 40-70 min after injection and scans were reconstructed via use of the ordered subset expectation maximization algorithm on a 4D volume with three frames (3 × 600 s). A 6-min transmission scan was promptly performed following each PET acquisition with a rotating Caesium-137point source to correct for attenuation. Moreover, each image was adjusted for dead time, decay, as well as random and scattered coincidences. T 1 -weighted images were corrected for non-uniformity and field distortion and then processed with an in-house pipeline. Subsequently, PET images were automatically registered to the T 1 -weighted image space and the T 1 -weighted images were linearly and nonlinearly registered to the Alzheimer's disease neuroimaging initiative template space. To reduce the risk of meningeal spillover within neighbouring brain regions, [ 18 F]-MK-6240 images were meninges-striped in native space prior to their transformations and blurring. 16 Next, a PET non-linear registration was carried out with linear and non-linear transformations from the T 1 -weighted image to the Alzheimer's disease neuroimaging initiative space and the PET to T 1 -weighted image registration with advanced normalization tools. PET images were spatially smoothed to obtain a final resolution of 8 mm full width at half maximum. The [ 18 F]-MK-6240 standardized uptake value ratio (SUVR) and [ 18 F]-AZD-4694 SUVR maps were developed by setting the reference region as the inferior cerebellar grey matter and cerebellar grey matter, respectively. A global estimated [ 18 F]-AZD-4694 SUVR value was obtained for each participant by averaging SUVR from the orbitofrontal, parietal, precuneus, prefrontal, temporal, anterior and posterior cingulate cortices. 17

Neuropsychological assessment
All participants in this study underwent the following clinical assessments: clinical dementia rating, cerebrovascular disease risk via the Hachinski ischaemic scale and mini-mental state examination. Neuropsychological memory exams were carried out by trained neuropsychologists. Memory scores were evaluated with the Rey auditory verbal learning test (RAVLT) and a logical memory test. 15

MRI acquisition and processing
Structural MRI data were obtained on a 3 T Siemens Magnetom using a standard head coil for all individuals at the Montreal Neurologic Institute. A fluid-attenuated inversion recovery sequence was also included in the MRI protocol, which was utilized to quantify white matter hyperintensity (WMH) volume. Freesurfer (v6.0) was used to quantify cortical thickness measurements. The Alzheimer's disease signature meta-region of interest was computed according to the weighted average of the bilateral entorhinal, inferior temporal, middle temporal and fusiform cortices. The WMH volume was determined via the lesion prediction algorithm as established in the LST toolbox version 2.0.15 in scientific principles of medicine, calculating a probability of WMH per voxel. A visual examination was performed for all segmented WMH images. Next, a binary WMH image was characterized for WMH probability > 0.5. 15

Statistical analysis
Baseline demographic and clinical data were evaluated using t-tests and χ 2 tests. Other statistical analyses were conducted via the R statistical software, version 3.5.3 with two-sided statistical significance set at α = 0.05. Descriptive statistics were written as frequency (%) for categorical variables; the mean [standard deviation (SD)] and median were reported for normally distributed numerical variables. For nonnormally distributed data, appropriate non-parametric tests were performed. A student's t-test and the non-parametric Wilcoxon-Mann-Whitney test were utilized to compare the memory scores between tau-positive and tau-negative individuals. Any missing values in the models were addressed through pairwise deletion (available case analysis). Multivariable linear regression was employed to assess the relationship between the change in logical memory and RAVLT scores and tau level from baseline to 12 months follow-up. A composite standardized measure of memory (logical memory, RAVLT) was obtained by calculating the Z-scores of each test and averaging the scores. 18 Standardized beta coefficients were reported for each model and the models were adjusted for the following covariants: age, sex, years of education and Aβ-PET levels. 18 Aβ-PET positivity at baseline was determined based on an

Baseline demographic characteristics
Demographic features of the study sample, including age and [ 18 F]-AZD-4694 and MRI-based atrophy clinical measures for all participants and by dichotomized tau groups, are presented in Table 1.

Discussion
This prospective cohort study examined the prognostic accuracy of tau-PET in predicting cognitive trajectories between groups stratified on tau neurofibrillary tangles in the medial temporal lobe {[ 18 F]-MK-6420} and neocortical Aβ plaques {[ 18 F]-AZD-4694} in relatively healthy, initially CU elderly individuals. The majority of subjects, 70% (n = 78), were categorized as A−T−, 8% (n = 9) as A−T+, 12% (n = 13) as A + T− and the remaining 10% (n = 11) as A + T + . A similar distribution was observed in a longitudinal observational study conducted by Betthauser et al. 6 , who also employed [ 18 F]-MK-6240 and focused on medial temporal tau, where 74% (n = 124) were classified as A−T−, 3% (n = 5) as A−T+, 14% (n = 23) as A + T− and 9% (n = 15) as A + T + . 20 While the proportion of A−T + individuals in our study is slightly higher than other recent in vivo PET studies, our findings may be attributable to the fact that tau abnormalities were defined based on medial temporal brain regions, which are considered to occur earlier than widespread neocortical tau abnormalities. 4,21 In neuropathological studies, tau abnormalities in early Braak regions in the absence of Aβ deposition are referred to as primary age-related tauopathy. 22 Our primary analysis showed a significant effect of Braak Stages I-II [ 18 F]-MK-6420 SUVR on change in the annual memory composite Z-score at baseline and longitudinally, independently of age, sex and neocortical Aβ-PET SUVR. Participants with pathological Aβ and medial temporal tau (A + T+) exhibited moderate cognitive decline over the follow-up period. No significant change was observed for the A−T+, A + T− and A−T− groups during the follow-up period, though it should be noted that the A−T + group was small. These results indicate that the accumulation of Aβ plaques and neurofibrillary tangles-detectable with PET-in early neurofibrillary tangle stage regions leads to abnormal cognitive decline during the preclinical stage of Alzheimer's disease. 23 This supports the use of PET biomarker stratification to define the construct of preclinical Alzheimer's disease and insinuates that the associated memory decline within this presymptomatic stage may begin earlier than previously suggested. 24 This also signifies that tau-PET can act as a powerful prognostic marker that can accurately predict rates of future cognitive decline, several years prior to clinical impairment. As such, our findings have implications for studies that examine the associations between Aβ and cognitive performance where assessments of tau pathology are not included. Levels of Aβ are poorly associated with the severity of dementia in Alzheimer's disease individuals, while tau neurofibrillary tangles levels are more closely associated with cognitive symptoms. 10 Given this information, the ability to measure tau burden in living persons is crucial in establishing an accurate diagnosis of Alzheimer's disease and predicting one's risk towards clinical progression. 25 Our results indicate that tau-PET may serve as a robust biomarker for the identification of Aβ-positive patients with tau-positivity (A + T+). 26 Since these individuals have a greater susceptibility to experiencing future cognitive decline, using this population for clinical trial designs would be beneficial for studying those at risk for Alzheimer's disease. 27 Some important derivations could be made based on our findings. First, incorporating tau-PET abnormalities as an inclusion criterion for recruitment in clinical trials would provide greater insight into the spatial topography of tauopathy and serve as a useful predictive model of cognitive decline. Some arguments could be made for the additional inclusion of tau pathology for Aβ monotherapy trials since it would help with obtaining a more targeted population. 28 Second, it is highly feasible when designing clinical trials to stratify participants based on the presence of early tau. Third, a longer duration of trials may be required during the preclinical or prodromal Alzheimer's disease stages to better observe differences in cognitive decline, as measured differences within one year may be too small. Fourth, tau aggregation outside the medial temporal lobe is also associated with more severe cognitive decline. Recent findings from our group demonstrate that the presence of tau in early Braak regions may have high sensitivity for capturing the risk of cognitive decline, whereas the accumulation of tau in more advanced Braak regions is associated with greater memory dysfunction. 16 Thus, clinical trials focusing on the symptomatic phases of Alzheimer's disease may wish to stratify subjects based on the presence of tau-PET abnormalities in more advanced Braak stages. Further neuroimaging research is merited to answer this particular question. Overall, our findings contribute to the body of literature that demonstrates the utility of tau-PET as an accurate predictor of cognitive trajectories for patients with preclinical Alzheimer's disease.
This study adds to the overall body of recent neuroimaging reports assessing Alzheimer's disease biomarkers in CU elderly. 6,7,9,11,29,30 It also supports recent findings that demonstrate tau-PET as an accurate prognostic marker in preclinical and prodromal Alzheimer's disease. 10 However, compared with these longitudinal studies, our study used the [ 18 F]-MK-6420 PET tracer, focusing on imaging the medial temporal regions for the detection of very early tau in CU individuals. Moreover, earlier work has highlighted that the topography of tau-PET uptake is associated with domain-specific cognitive decline. 31 More recent work has also provided evidence for tau-PET association with executive dysfunction in CU individuals. 7 Thus, it should be noted that tau-PET can be used to capture cognitive decline in different domains as well.
Future work should include a larger sample size, a longer study period and be paired with other tests of other cognitive domains to assess whether there will be an improvement in the accuracy of tau-PET as a prognostic marker for preclinical Alzheimer's disease.
Presently, both Aβ plaques and tau neurofibrillary tangles can be detected in vivo using PET imaging techniques, allowing for the spatiotemporal characterization of these biomarkers during one's lifetime. 6,7 With Aβ tracers -18 F-florbetapir, 18 F-flutemetamol and 18 F-florbetabenand the first tau tracer, 18 F-flortaucipir, recently approved by the FDA, Alzheimer's disease molecular imaging is transitioning from a preclinical modality towards a fully clinically useful tool. 5 This new technique can improve the diagnostic accuracy of our present clinical criteria when assessing individuals with cognitive impairment, which currently has limited sensitivity and specificity relative to autopsy. 5 The strengths of this study include its longitudinal cohort design, use of multimodal imaging (Aβ-PET and tau-PET) and availability of longitudinal logical memory and RAVLT scores. However, some methodological limitations must be considered when interpreting this study. The first is that the memory tests used were written in French, which may not be well validated for non-English participants. Moreover, it is important to note that the Translational Biomarkers in Ageing and Dementia cohort is a convenience sample of individuals who are motivated to participate in a study about ageing and dementia, therefore introducing recruitment and sampling biases. Another shortcoming is the limited post-mortem data available for the [ 18 F]-MK-6420 tau-PET tracer. 14 A greater availability of autopsy studies would help with our understanding of the extent to which [ 18 F]-MK-6240 binds to tau neurofibrillary tangle levels. Additionally, the memory tests used in this study are standard. There are other tests that may be more optimally positioned and sensitive to detect very early cognitive changes in CU individuals. It is also important to emphasize that tau abnormality in the present study was defined based on medial temporal brain regions, which may partially account    for the higher proportion of A-T + reported in our study, as compared with other recent PET imaging studies. 4 Future studies should address whether APOEɛ4 genotype independently predicts prospective cognitive decline beyond Aβ-PET and tau-PET levels, given the association between APOEɛ4 genotype and both Aβ-PET and medial temporal tau-PET. Furthermore, our study did not investigate changes in diagnosis (i.e. CU to mild cognitive impairment) and it was correspondingly not possible to determine hazard ratios for clinical progression. Therefore, larger studies with longer follow-up durations are warranted.

Conclusion
In this prognostic study, the [ 18 F]-MK-6240 tau-PET tracer showed strong prognostic utility as an accurate predictor of longitudinal cognitive change, especially in cognitively unimpaired individuals during the preclinical stage of Alzheimer's disease.